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Preface Acknowledgments Dear Students 1. An Introduction to Business Statistics 1.1 Business Statistics and Their Uses 1.2 Data 1.3 Descriptive and Inferential Statistics 1.4 Ethics and Statistics—It’s a Dangerous World of Data Out There 2. Displaying Descriptive Statistics 2.1 The Role Technology Plays in Statistics 2.2 Displaying Quantitative Data 2.3 Displaying Qualitative Data 2.4 Contingency Tables 2.5 Stem and Leaf Display 2.6 Scatter Plots 3. Calculating Descriptive Statistics 3.1 Measures of Central Tendency 3.2 Measures of Variability 3.3 Using the Mean and Standard Deviation Together 3.4 Working with Grouped Data 3.5 Measures of Relative Position 3.6 Measures of Association Between Two Variables 4. Introduction to Probabilities 4.1 An Introduction to Probabilities 4.2 Probability Rules for More Than One Event 4.3 Counting Principles 5. Discrete Probability Distributions 5.1 Introduction to Discrete Probability Distributions 5.2 Binomial Distributions 5.3 Poisson Distributions 5.4 The Hypergeometric Distribution 6. Continuous Probability Distributions 6.1 Continuous Random Variables 6.2 Normal Probability Distributions 6.3 Exponential Probability Distributions 6.4 Uniform Probability Distributions 7. Sampling and Sampling Distributions 7.1 Why Sample? 7.2 Types of Sampling 7.3 Sampling and Nonsampling Errors 7.4 The Central Limit Theorem 7.5 The Sampling Distribution of the Proportion 8. Confidence Intervals 8.1 Point Estimates 8.2 Calculating Confidence Intervals for the Mean when the Standard Deviation (σ) of a Population Is Known 8.3 Calculating Confidence Intervals for the Mean when the Standard Deviation (σ) of a Population Is Unknown 8.4 Calculating Confidence Intervals for Proportions 8.5 Determining the Sample Size 8.6 Calculating Confidence Intervals for Finite Populations 9. Hypothesis Testing for a Single Population 9.1 An Introduction to Hypothesis Testing 9.2 Hypothesis Testing for the Population Mean When σ Is Known 9.3 Hypothesis Testing for the Population Mean when σ Is Unknown 9.4 Hypothesis Testing for the Proportion of a Population 9.5 Type II Errors 10. Hypothesis Tests Comparing Two Populations 10.1 Comparing Two Population Means with 10.2 Comparing Two Population Means with 10.3 Hypothesis Testing With Dependent Samples 10.4 Comparing Two Population Proportions with Independent Samples 11. Analysis of Variance (ANOVA) Procedures 11.1 One-Way ANOVA: Examining the Effect a Single Factor Has on the Means of Populations 11.2 Randomized Block ANOVA: Examining the Effects of a Single Factor by Blocking a Second Factor 11.3 Two-Way ANOVA: Examining the Effects Two Factors Have on the Means of Populations 12. Chi-Square Tests 12.1 Comparing Two or More Population Proportions 12.2 Determining If Observed Frequencies Follow a Known Probability Distribution 12.3 Testing the Independence of Two Variables 13. Hypothesis Tests for the Population Variance 13.1 Testing the Variance of a Single Population 13.2 Comparing the Variances of Two Populations 14. Correlation and Simple Linear Regression 14.1 Dependent and Independent Variables 14.2 Correlation Analysis 14.3 Simple Linear Regression Analysis 14.4 Using a Regression to Make a Prediction 14.5 Testing the Significance of the Slope of the Regression Equation 14.6 Assumptions for Regression Analysis 14.7 A Simple Regression Example with a Negative Correlation 14.8 Some Final (but Very Important) Thoughts 15. Multiple Regression and Model Building 15.1 Developing the Multiple Regression Model 15.2 Explaining the Variation of the Dependent Variable 15.3 Inferences about the Independent Variables 15.4 Using Qualitative Independent Variables 15.5 Model Building 16. Forecasting 16.1 Introduction to Forecasting 16.2 Smoothing Forecasting Methods 16.3 Forecasting with Regression Analysis 16.4 Forecasting with Seasonality 17. Decision Analysis 17.1 Introduction to Decision Analysis 17.2 Constructing a Decision Table 17.3 Decision Making Under Uncertainty 17.4 Decision Making Under Risk 17.5 Decision Making Using Decision Trees 17.6 Using Bayes’ Theorem to Calculate Posterior Probabilities 18. Nonparametric Statistics 18.1 Introduction to Nonparametric Statistics 18.2 The Sign Test 18.3 The Wilcoxon Rank-Sum Test for Two Independent Samples 18.4 The Wilcoxon Signed-Rank Test for Two Dependent Samples 18.5 The Kruskal-Wallis One-Way ANOVA 18.6 The Spearman Rank-Order Correlation Coefficient Appendix A Table 1 Binomial Probabilities Table 2 Poisson Probabilities Table 3 Cumulative Probabilities for the Standard Normal Distribution Table 4 Cumulative Probabilities for the Standard Normal Distribution Table 5 Student’s t-distribution Table 6 F-distribution Table 7 Critical Values of the Studentized Range, Q Table 8 Chi–Square Distribution Table 9 Critical Values for the Durbin-Watson Statistic Appendix B: Answers to Selected Even-Numbered Problems Index of Applications Index Table of Contents
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